X-Git-Url: http://gitweb.michael.orlitzky.com/?a=blobdiff_plain;f=dunshire%2Fgames.py;h=e25db28a8e7349e88b9bdd18f16d0eea0b5c03c1;hb=d988995ea403db9d6f63a7101d31b8d624fc379e;hp=c841caae752b9075ee28030d2a15df5d42354308;hpb=3ee9db27adb69d68871ef26ec22ef144f351e99d;p=dunshire.git

diff --git a/dunshire/games.py b/dunshire/games.py
index c841caa..e25db28 100644
--- a/dunshire/games.py
+++ b/dunshire/games.py
@@ -346,7 +346,7 @@ class SymmetricLinearGame:
                           str(self._K),
                           indented_e1,
                           indented_e2,
-                          self._condition())
+                          self.condition())
 
 
     def _zero(self):
@@ -505,7 +505,13 @@ class SymmetricLinearGame:
             # objectives match (within a tolerance) and that the
             # primal/dual optimal solutions are within the cone (to a
             # tolerance as well).
-            if abs(p1_value - p2_value) > options.ABS_TOL:
+            #
+            # The fudge factor of two is basically unjustified, but
+            # makes intuitive sense when you imagine that the primal
+            # value could be under the true optimal by ``ABS_TOL``
+            # and the dual value could be over by the same amount.
+            #
+            if abs(p1_value - p2_value) > 2*options.ABS_TOL:
                 raise GameUnsolvableException(self, soln_dict)
             if (p1_optimal not in self._K) or (p2_optimal not in self._K):
                 raise GameUnsolvableException(self, soln_dict)
@@ -513,7 +519,7 @@ class SymmetricLinearGame:
         return Solution(p1_value, p1_optimal, p2_optimal)
 
 
-    def _condition(self):
+    def condition(self):
         r"""
         Return the condition number of this game.
 
@@ -541,7 +547,7 @@ class SymmetricLinearGame:
         >>> e1 = [1]
         >>> e2 = e1
         >>> SLG = SymmetricLinearGame(L, K, e1, e2)
-        >>> actual = SLG._condition()
+        >>> actual = SLG.condition()
         >>> expected = 1.8090169943749477
         >>> abs(actual - expected) < options.ABS_TOL
         True